m6A reading protein RBMX as a biomarker for prognosis and tumor progression in esophageal cancer

Background

As a member of m6A methylated binding protein, RNA binding motif protein X-linked (RBMX) has been reported to be associated with tumor invasion, metastasis and prognosis. However, the prognostic significance of RBMX expression in esophageal cancer (ESCA) remains unclear.

Methods

Based on the TIMER database, GEPIA database, cBioPortal database, CIBERSORT deconvolution algorithm, String-DB database, LinkedOmics database, etc., the RBMX expression level, mRNA expression level, prognostic relationship, genetic mutation, immune cell infiltration level, protein interaction network, differential co-expression genes and functional enrichment in esophageal carcinoma were analyzed. Immunohistochemistry was used to detect the expression of RBMX in 53 cases of esophageal carcinoma and adjacent esophageal tissues.

Results

The RBMX expression in ESCA tissue was significantly higher than that in the normal tissues. The overall survival (OS) of patients with high RBMX expression was significantly lower than that of patients with low expression (P=0.04). The protein encoded by the RBMX gene appeared to copy number amplification, mutation and deep deletion. The expression level of RBMX was positively correlated with the levels of follicular helper T cells, eosinophils and initial B cells (P<0.05). Genes significantly and positively correlated with RBMX expression included HNRNPA1L2, SFRS13A, HNRNPA1, etc., which were mainly enriched in biological processes (BPs) such as cell division, mRNA splicing, RNA binding and mRNA 3'-UTR binding.

Conclusions

RBMX may be as a biomarker of poor prognosis of ESCA. RBMX is closely related to the survival and prognosis, genetic mutation and immune cell infiltration of patients with ESCA.

Seven Fatty Acid Metabolism-Related Genes as Potential Biomarkers for Predicting the Prognosis and Immunotherapy Responses in Patients with Esophageal Cancer

Background: Esophageal cancer (ESCA) is a major cause of cancer-related mortality worldwide. Altered fatty acid metabolism is a hallmark of cancer. However, studies on the roles of fatty acid metabolism-related genes (FRGs) in ESCA remain limited. Method: We identified differentially expressed FRGs (DE-FRGs). Then, the DE-FRGs prognostic model was constructed and validated using a comprehensive analysis. Moreover, the correlation between the risk model and clinical characteristics was investigated. A nomogram for predicting survival was established and evaluated. Subsequently, the difference in tumor microenvironment (TME) was compared between two risk groups. The sensitivity of key DE-FRGs to chemotherapeutic interventions and their correlation with immune cells were investigated. Finally, DEGs between two risk groups were measured and the prognostic value of key DE-FRGs in ESCA was confirmed in other databases. Results: A prognostic model was constructed based on seven selected DEG-FRGs. TNM staging and CD8+ T cells were significantly correlated with high-risk groups. Low-risk groups exhibited more infiltrated M0 macrophages, an activation of type II interferon (IFN-γ) responses, and were found to be more suitable for immunotherapy. Seven key DE-FRGs with prognostic value were found to be considerably influenced by different chemotherapy drugs. Conclusion: A prognostic model based on seven DE-FRGs may efficiently predict patient prognosis and immunotherapy response, helping to develop individualized treatment strategies in ESCA.

Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma

The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of potential drug target genes between SCC and AC is crucial for more effective treatment of these diseases, given the high toxicity of chemotherapy and resistance to administered medications. Herein we attempted to identify and rank differentially expressed genes (DEGs) in SCC vs. AC using ensemble feature selection methods. RNA-seq data from The Cancer Genome Atlas and the Fudan-Taizhou Institute of Health Sciences (China). Six feature filters algorithms were used to identify DEGs. We built robust predictive models for histological subtypes with the random forest (RF) classification algorithm. Pathway analysis also be performed to investigate the functional role of genes. 294 informative DEGs (87 of them are newly discovered) have been identified. The areas under receiver operator curve (AUC) were higher than 99.5% for all feature selection (FS) methods. Nine genes (i.e., ERBB3, ATP7B, ABCC3, GALNT14, CLDN18, GUCY2C, FGFR4, KCNQ5, and CACNA1B) may play a key role in the development of more directed anticancer therapy for SCC and AC patients. The first four of them are drug targets for chemotherapy and immunotherapy of esophageal cancer and involved in pharmacokinetics and pharmacodynamics pathways. Research identified novel DEGs in SCC and AC, and detected four potential drug targeted genes (ERBB3, ATP7B, ABCC3, and GALNT14) and five drug-related genes.

Bioinformatics analysis identifying FBXO45 gene as a potential oncogene in esophageal cancer

BACKGROUND

F-box protein 45 (FBXO45) is a member of the F-box protein family, and is reportedly involved in the progression of many diseases. However, its role in esophageal cancer (ESCA) remains unclear.

METHODS

The expression, clinical characteristics, gene function, pathway, and correlation between the infiltration of different immune cells were analyzed using public data. The pan-cancer expression of FBXO45 was assessed using the TIMER2 database. The expression of FBXO45 in different tumor stages and histology subtypes were evaluated using the UALCAN database. The protein-protein interaction (PPI) network was constructed using the STRING database. Immune cell infiltration data were downloaded from the ImmuCellAI database.

RESULTS

The top 300 genes most positively correlated with FBXO45 were screened into the enrichment analysis. The functional enrichment results showed that FBXO45 was mainly associated with proteasomal protein catabolic process and the regulation of DNA metabolic processing in the biological process (BP) category; spindle, chromosomal region, and focal adhesion in the cellular component category; and ATPase activity and ubiquitin-protein transferase activity terms in the molecular function category. FBXO45 was overexpressed in ESCA and other cancer types. FBXO45 expression was positively associated with the infiltration levels of immunosuppressive cells, such as CD8+ (cluster of differentiation 8+) T cells and NK (natural killer cell) cells, in ESCA. MYCBP2 and SKP1 were most associated with FBXO45.

CONCLUSIONS

Our results suggested that FBXO45 is a potential oncogene in ESCA. Elevated FBXO45 expression indicates a relatively immunosuppressive microenvironment.